semi-supervised learning for molecular property prediction
requried package: tensorflow==2.3.0,rdkit==2020.03.2,numpy==1.18.5,pandas==1.1.0, openbabel==2.3.1
-- pretrain: contains the codes for masked atom prediction pre-training task.
-- classification and regression: contain the code for fune-tuning on specified tasks
-- dataset: contain the code to building dataset for pre-traing and fine-tuning
-- utils: contain the code to convert molecules to graphs
--data: data used for pretraining and fine-tuning
User should first unzip the data file and place it in the right place. Then pre-training the MG-BERT for 10~20 epoch. After that, the classification or the regression file is used to predict specific molecular property.